Bee Dagum Seasonal Adjustment Methods and Real Time Trend-Cycle Estimation 9783319318202

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Автор: Bee Dagum
Название: Seasonal Adjustment Methods and Real Time Trend-Cycle Estimation
ISBN: 9783319318202
Издательство: Springer
Классификация:

Социальные исследования и статистика

Макроэкономика

Эконометрика

Вероятность и статистика

ISBN-10: 3319318209
Обложка/Формат: Hardback
Страницы: 283
Вес: 0.61 кг.
Дата издания: 2016
Серия: Statistics for Social and Behavioral Sciences
Язык: English
Издание: 1st ed. 2016
Иллюстрации: 10 illustrations, color; 42 illustrations, black and white; xvi, 283 p. 52 illus., 10 illus. in color.
Размер: 234 x 156 x 18
Читательская аудитория: General (us: trade)
Основная тема: Statistics / Business, Economics, and Management
Ссылка на Издательство: Link
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Поставляется из: Германии
Описание: This book explores widely used seasonaladjustment methods and recent developments in real time trend-cycle estimation.It discusses in detail the properties and limitations of X12ARIMA, TRAMO-SEATSand STAMP - the main seasonal adjustment methods used by statistical agencies. Several real-world cases illustrate eachmethod and real data examples can be followed throughout the text. Thetrend-cycle estimation is presented using nonparametric techniques based onmoving averages, linear filters and reproducing kernel Hilbert spaces, takingrecent advances into account. The book provides a systematical treatment ofresults that to date have been scattered throughout the literature.Seasonal adjustment and real timetrend-cycle prediction play an essential part at all levels of activity inmodern economies. They are used by governments to counteract cyclicalrecessions, by central banks to control inflation, by decision makers forbetter modeling and planning and by hospitals, manufacturers, builders,transportation, and consumers in general to decide on appropriate action.This book appeals to practitioners ingovernment institutions, finance and business, macroeconomists, and other professionalswho use economic data as well as academic researchers in time series analysis,seasonal adjustment methods, filtering and signal extraction. It is also usefulfor graduate and final-year undergraduate courses in econometrics and timeseries with a good understanding of linear regression and matrix algebra, aswell as ARIMA modelling.
Дополнительное описание: Introduction.- Time Series Components.- Part I: Seasonal Adjustment Methods.- Seasonal Adjustment: Meaning, Purpose and Methods.- Linear Filters Seasonal Adjustment Methods: Census Method II and its Variants.- Seasonal Adjustment Based on ARIMA Decomposit

Seasonal Adjustment Methods and Real Time Trend-Cycle Estimation, Bee Dagum